{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Kanerva's Figure 1.2 (page 25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sdm as sdmlib\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import clear_output\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "bits = 1000\n",
    "sample = 1000000\n",
    "\n",
    "address_space = sdmlib.AddressSpace.init_random(bits, sample)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_probabilities():\n",
    "    from math import factorial\n",
    "    comb = lambda a, b: factorial(a)/factorial(b)/factorial(a-b)\n",
    "    acc = [0]\n",
    "    for i in xrange(1001):\n",
    "        acc.append(acc[-1] + comb(1000, i))\n",
    "    x = range(0, 1001)\n",
    "    y = [acc[i]/float(2**1000) for i in xrange(1001)]\n",
    "    return x, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106c79f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x, y = calculate_probabilities()\n",
    "plt.plot(x, y);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run(radius):\n",
    "    x = range(0, 1001)\n",
    "    y = []\n",
    "    for i, dist in enumerate(x):\n",
    "        clear_output(wait=True)\n",
    "        print 'Distance: {:4d} ({:.2f}%)'.format(dist, 100.*(i+1)/len(x))\n",
    "        \n",
    "        b1 = sdmlib.Bitstring.init_random(bits)\n",
    "        b2 = sdmlib.Bitstring.init_from_bitstring(b1)\n",
    "        b2.flip_random_bits(dist)\n",
    "        assert b1.distance_to(b2) == dist\n",
    "    \n",
    "        h1 = set(address_space.scan_thread(b1, radius, 4))\n",
    "        h2 = set(address_space.scan_thread(b2, radius, 4))\n",
    "        \n",
    "        y.append(len(h1&h2))\n",
    "    return x, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "v = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance: 1000 (100.00%)\n"
     ]
    }
   ],
   "source": [
    "v.append((451, run(451)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance: 1000 (100.00%)\n"
     ]
    }
   ],
   "source": [
    "v.append((480, run(480)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance: 1000 (100.00%)\n"
     ]
    }
   ],
   "source": [
    "v.append((500, run(500)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Python/2.7/site-packages/ipykernel_launcher.py:2: MatplotlibDeprecationWarning: pyplot.hold is deprecated.\n",
      "    Future behavior will be consistent with the long-time default:\n",
      "    plot commands add elements without first clearing the\n",
      "    Axes and/or Figure.\n",
      "  \n",
      "/Library/Python/2.7/site-packages/ipykernel_launcher.py:11: MatplotlibDeprecationWarning: pyplot.hold is deprecated.\n",
      "    Future behavior will be consistent with the long-time default:\n",
      "    plot commands add elements without first clearing the\n",
      "    Axes and/or Figure.\n",
      "  # This is added back by InteractiveShellApp.init_path()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108093310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6), dpi=100)\n",
    "plt.hold(True)\n",
    "for d, points in v[:-1]:\n",
    "    x, y = points\n",
    "    ymax = max(y)\n",
    "    y = [float(a)/ymax for a in y]\n",
    "    plt.plot(x, y, label='Radius: {}'.format(d))\n",
    "plt.xlabel('Distance between two random bitstrings')\n",
    "plt.ylabel('Intersection of their circles')\n",
    "plt.legend()\n",
    "plt.hold(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
